Fill-Mask
Transformers
PyTorch
English
babylm
babylm-2026
gpt-bert
sample-efficient-pretraining
muon
custom_code
Instructions to use svsatheesh/BabySteps_SidBert-100M-mixed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use svsatheesh/BabySteps_SidBert-100M-mixed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="svsatheesh/BabySteps_SidBert-100M-mixed", trust_remote_code=True)# Load model directly from transformers import GPTBERTFoCausalLM model = GPTBERTFoCausalLM.from_pretrained("svsatheesh/BabySteps_SidBert-100M-mixed", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c24c400d6c220f929f2089b2f299b6c1e3a1576d70ba2d13660be094afcac566
- Size of remote file:
- 5.5 MB
- SHA256:
- 8dd4cb59a68a464fe888998c101004ec1e682cb305e548f28296af752d10270b
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